Data Analyst Agent

The Data Analyst Agent is a specialized AI assistant that helps you query, visualize, and surface data across the GitLab platform. It uses GitLab Query Language (GLQL) to retrieve and analyze data, then provides clear, actionable insights about your projects and teams.

Use the Data Analyst Agent when you need help with:

• Volume analysis: Counting merge requests, issues, or other work items over time periods.
• Team performance: Understanding what team members have worked on and their output.
• Trend analysis: Identifying patterns in your development workflow.
• Status monitoring: Checking the state of work items across your project or group.
• Work item discovery: Finding issues, merge requests, or epics by author, label, milestone, or other criteria.
• GLQL query generation: Creating queries to embed anywhere that supports GitLab Flavored Markdown, including issues, merge requests, epics, comments, wikis, snippets, and releases.

You can leave feedback in issue 574028.

Known issues

• The agent can perform light aggregation on queried data, but results may be incomplete for datasets exceeding 100 items.
• GLQL supports querying specific areas but not all GitLab data sources.
• The agent cannot output directly to work items or dashboards. However, you can copy the generated GLQL queries and embed them on any page that supports GitLab Flavored Markdown.

Access the Data Analyst Agent

Prerequisites:

• Foundational agents must be turned on.

1. Open GitLab Duo Chat:

   On the GitLab Duo sidebar, select either New GitLab Duo Chat ( ) or Current GitLab Duo Chat ( ).

   A Chat conversation opens in the GitLab Duo sidebar on the right side of your screen.

2. From the New chat ( ) dropdown list, select Data Analyst.

3. Enter your analytics question or request. To get the best results from your request:

   • Specify the scope (project or group) when asking about data.
   • Include time ranges for time-based analysis.
   • Be specific about the type of work items you’re interested in.

Example prompts

• Volume and counting:
  • “How many merge requests were merged this month?”
  • “Count the issues created last week.”
  • “How many bugs are currently open?”
• Team performance:
  • “What has @username worked on this month?”
  • “Show me merge requests merged by team X in the last two weeks.”
  • “Show me a table of issues with titles and labels assigned to me.”
  • “List open merge requests by author.”
• Status and monitoring:
  • “Show me open issues with ~priority::1 and ~bug labels.”
  • “Show me overdue issues.”
  • “What merge requests are waiting for review?”
  • “List issues in the current milestone.”
• Trend analysis:
  • “Show me the merge request activity over the last month.”
  • “What’s the trend of bug creation this quarter?”
  • “Compare issue closure rates between this month and last month.”
• GLQL query generation:
  • “Write a GLQL query for open issues assigned to me.”
  • “Create a table showing all merge requests merged this week.”
  • “Generate a GLQL embedded view for team X’s open work.”
  • “What’s the GLQL syntax for filtering by multiple labels?”
• Work item discovery:
  • “List merge requests targeting the main branch.”
  • “Find issues updated in the last 24 hours.”
  • “Show me open bugs assigned to team X.”